scholarly journals A Proposed Model for Detecting Learning Styles Based on Agent Learning

2016 ◽  
Vol 11 (10) ◽  
pp. 65 ◽  
Author(s):  
M S Hasibuan ◽  
L E Nugroho ◽  
P I Santosa ◽  
S S Kusumawardani
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Evaluation Model ◽  
Learning System ◽  
Learning Activities ◽  
Instructional Materials ◽  
Data Driven ◽  
Automatic Learning ◽  
Proposed Model ◽  
Agent Learning

A learning style is an issue related to learners. In one way or the other, learning style could assist learners in their learning activities if students ignore their learning styles, it may influence their effort in understanding teaching materials. To overcome these problems, a model for reliable automatic learning style detection is needed. Currently, there are two approaches in detecting learning styles: data driven and literature based. Learners, especially those with changing learning styles, have difficulties in adopting these two approach since they are not adaptive, dynamic and responsive (ADR). To solve the above problems, a model using agent learning approach is proposes. Agent learning involves performing activities in four phases, i.e. initialization, learning, matching and, recommendations to decide the learning styles the students use. The proposed system will provide instructional materials that match the learning style that has been detected. The automatics detection process is performed by combining the data-driven and literature-based approaches. We propose an evaluation model agent learning system to ensure the model is working properly.

An Exploratory Model of Learning Styles Based on Agent Learning

2018 ◽  
Vol 2 (2) ◽  
Author(s):  
Ayse Kok Arslan
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Learning Activities ◽  
Data Driven ◽  
Learning Approach ◽  
Teaching Materials ◽  
Automatic Learning ◽  
Detection Model ◽  
Combining Data ◽  
Agent Learning

<p><strong><em>Abstract—A </em></strong><strong>learning style is an issue related to learners. In one way or the other, learning styles could assist learners in their learning activities. If the learners ignore their learning styles, it may influence their effort in understanding teaching materials. To overcome these problems, a model for reliable automatic learning style detection is needed. Currently, there are two approaches in automatically detecting learning styles: data driven and literature based. Learners, especially those with changing learning styles, have difficulties in adopting these two approaches since they are not adaptive, dynamic and responsive (ADR). To solve the above problems, a model using agent learning approach is proposed. Agent learning performs four phased activities, i.e. initialization, learning, matching and recommendations to decide which learning styles are used by the students. Furthermore, the system will provide teaching materials which are appropriate for the detected learning style. The detection process is performed automatically by combining data-driven and literature-based approaches. The detected learning style used for this research is VARK (Visual, Auditory, Read/Write, and Kinesthetic). This learning style detection model is expected to optimize the learners in adhering with the online learning.</strong><strong></strong></p>

Reality and Diversity: Reform in the Architectural Design Studio

2006 ◽  
Vol 31 (2) ◽  
pp. 20-31
Author(s):  
Jia Beisi
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Personal Experience ◽  
Architectural Design ◽  
Learning Activities ◽  
Two Dimensional ◽  
Learning Style Inventory ◽  
Reflection In Action ◽  
Architectural Design Studio ◽  
And Performance

Habraken points out that the architectural studio failed to bring students to basic questions in the architecture of everyday environments. Till criticizes that in a studio, it is only the professional value represented by the teachers that prevails. To investigate the reasons of the allegation, this paper introduces a learning model defined by David A. Kolb, in which a learning process consists of two dimensional movements: i.e., prehension (concrete experiences vs. abstract conceptualization) and transformation (reflection and experiment). The paper then inquires into Schön's observation in the studio learning mode characterized as reflection-in-action. It is found that this studio is mainly dealing with the transformation dimension, and prehension dimension is either suppressed or represented by the teacher's experiences and conceptions. The paper discovers that the cause of problems raised by Habraken and Till is the inherent lack of substance in the prehension dimension. The paper assesses a studio programme in which the basic questions of built environment were systematically introduced. It analyzes the students' reactions and performance in line with students' learning styles found using Kolb's Learning Style Inventory (LSI). It suggests that the students' learning activities are more diversified than what Schön could perceive. There is a possibility to adapt students' personal experience and abstract conceptualization which may play into the studio. By enhancing diversity of learning styles rather than letting one's learning style (reflection-in-action) prevail, the studio may become a platform in which students may learn from each other.

Visual-Based Resources for Teaching

2010 ◽  
pp. 112-121
Author(s):  
Lawrence A. Tomei
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Web Sites ◽  
Instructional Strategy ◽  
Visual Media ◽  
Individual Learning ◽  
Instructional Materials ◽  
Multimedia Environment ◽  
Power Point ◽  
Slide Shows

Research has found that students learn better when they rely on the instructional strategy best suited to their own particular learning style (Fitzsimmons, 1996). While concrete learners depend on the text-based workbook for reinforcement, abstract learners find visual media more to their liking. Microsoft Power Point creates presentations suitable for the classroom by offering a multimedia environment for concepts and ideas important for understanding. It provides a suite of tools to create powerful slide shows incorporating bulleted lists and numbered text; multimedia clip art, pictures, sounds, and movies; links to teacher-validated web sites, programs, and documents; colorful charts and graphs; and, a choice of output options tailored to individual learning styles. Power Point offers an extensive fare of commands, options, and menus. With the advanced features of auto content wizard, hyperlinks, and printing alternatives, it also provides an array of all the tools necessary to build truly exciting and interactive instructional materials.

A Model for an Adaptive Hypermedia Learning System Based on Data Mining Technique

2017 ◽  
pp. 65-85
Author(s):  
Mahnane Lamia ◽  
Mohamed Hafidi
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Personal Characteristics ◽  
Learning Objects ◽  
Learning System ◽  
Learning Performance ◽  
Adaptive Hypermedia ◽  
Data Mining Technique ◽  
Pedagogical Strategies ◽  
Hypermedia Learning

Since the learning style of each learner is different. Adaptive hypermedia learning system (AHLS) must fit different learner's needs. A number of AHLS have been developed to support learning styles as a source for adaptation. However, these systems suffer from several problems, namely: less attention was paid to the relationship between learning styles and learning performance. This paper proposes an AHLS model based on learning styles and learning performance. On one hand, the developed prototype will assist a learner in accessing and using learning resources which are adapted according to his/her personal characteristics (in this case his/her learning style and level of knowledge). On the other hand, it will facilitate the learning content teacher in the creation of appropriate learning objects and their application to suitable pedagogical strategies.

The Learning Style-Based Adaptive Learning System Architecture

2015 ◽  
Vol 5 (2) ◽  
pp. 1-10 ◽  
Author(s):  
Chyun-Chyi Chen ◽  
Po-Sheng Chiu ◽  
Yueh-Min Huang
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Adaptive Learning ◽  
System Architecture ◽  
Learning System ◽  
Learning Materials ◽  
Learning Path ◽  
Different Types ◽  
Learning System Architecture ◽  
Adaptive Learning System

In the current study of learning process that show learners will take a different way and use different types of learning resources in order to learning better. Any many researchers also agree that learning materials must be able to meet the various learning styles of learners. Therefore, let learners can effective to improve their learning, for different learning styles of learners should be given different types of learning materials. In this paper the authors propose a learner's learning style-based adaptive learning system architecture that is designed to help learners advance their on-line learning along an adaptive learning path. The investigation emphasizes the relationship of learning content to the learning style of each participant in adaptive learning. An adaptive learning rule was developed to identify how learners of different learning styles may associate those contents which have the higher probability of being useful to form an optimal learning path. In this adaptive learning system architecture, it will according to different learning styles given different types of learning materials and will according to learner's profile to adjust learner's learning style for providing suitable learning materials.

scholarly journals SCIENCE EDUCATION ADAPTIVE LEARNING SYSTEM AS A COMPUTER-BASED SCIENCE LEARNING WITH LEARNING STYLE VARIATIONS

2018 ◽  
Vol 17 (4) ◽  
pp. 711-727 ◽  
Author(s):  
Zulfiani Zulfiani ◽  
Iwan Permana Suwarna ◽  
Sujiyo Miranto
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Adaptive Learning ◽  
Science Learning ◽  
Learning System ◽  
Learning Material ◽  
Learning Approaches ◽  
Slow Learners ◽  
Computer Based ◽  
Adaptive Learning System

Students with their different learning styles also have their own different learning approaches, and teachers cannot simultaneously facilitate them all. Teachers’ limitation in serving all students’ learning styles can be anticipated by the use of computer-based instructions. This research aims to develop ScEd-Adaptive Learning System (ScEd-ASL) as a computer-based science learning media by accommodating students’ learning style variations. The research method used is a mixed method at junior high schools in Tangerang Selatan. The final product of the research is a special learning media appropriate to students’ visual, aural, read/write and kinesthetic learning styles. The uniqueness of the media is its form of integrated science materials, accommodating fast and slow learners, and appropriate to their learning styles. ScEd-Adaptive Learning System as a developed computer-based science learning media was declared as good and valid by four media experts and five learning material experts. ScEd-ALS for kinesthetic style has a high effectivity to improve students learning mastery (100%), consecutively aural (63%), read/write (55%), and visual (20%). This media development can be continued with the Android version or iOS to make it more operationally practical. Keywords: adaptive learning system, science learning media, computer-based instruction, learning style.

scholarly journals Learning Styles and Dyslexia Types – Understanding Their Relationship and its Benefits in Adaptive E-learning Systems

2020 ◽  
Vol 14 (15) ◽  
pp. 25
Author(s):  
Aisha Y Alsobhi ◽  
Khaled H Alyoubi
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Learning Systems ◽  
Learning System ◽  
Knowledge Level ◽  
Educational Establishment ◽  
E Learning ◽  
User Learning ◽  
The Relationship ◽  
Better Than

Learning is a fundamental element of people’s everyday lives. Learning experiences can take the form of our interactions with others, through attending an educational establishment, etc. Not everyone learns in the same way, and even people who are considered to have a similar standard of abilities or proficiency will exhibit different learning styles. This does not necessarily mean that some students are better than others; it means that students are different from one another. Adaptive e-learning system should be capable of adapting the content to the user learning style, abilities and knowledge level. In this paper, we investigate the benefits of incorporating learning styles and dyslexia type in adaptive e-learning systems. Adaptivity aspects based on dyslexia type and learning styles enrich each other, enabling systems to provide learners with materials which fit their needs more accurately. Besides, consideration of learning styles and dyslexia type can contribute to more accurate student modelling. In this paper, the relationship between learning styles, the Felder–Silverman learning style model (FSLSM), and dyslexia type, is investigated. These relationships will lead to a more reliable student model.

scholarly journals Effects of Learning Styles on Self-directed Foreign Language Vocabulary Learning

2014 ◽  
pp. 112-126
Author(s):  
Jing Wu
Keyword(s):  
Individual Differences ◽  
Learning Styles ◽  
Learning Strategies ◽  
Learning Style ◽  
Vocabulary Learning ◽  
Mainland China ◽  
Learning System ◽  
Vocabulary Learning Strategies ◽  
Learning Paths ◽  
Foreign Language Vocabulary Learning

Vocabulary learning is an on-going and life-long process, which is greatly influenced by individual differences. It has been noted that there is inefficient self-directed FL vocabulary learning of college students in mainland China and non-individualized learning may be one of the major reasons. As one of the most significant individual differences, a student’s learning style is supposed to largely determine their selection of learning strategies and have an effect on learning outcomes. This paper focuses on categorizing diversified vocabulary learning tasks which activate various vocabulary learning strategies, and integrating them into a learning system along particular learning paths to cater for different learning styles. The system is also tested in an empirical study for the purpose of checking the effects of these learning paths.

scholarly journals Applying adaptive learning by integrating semantic and machine learning in proposing student assessment model

2022 ◽  
Vol 12 (2) ◽  
pp. 2014
Author(s):  
Kamilia Hosny ◽  
Abeer El-korany
Keyword(s):  
Machine Learning ◽  
Learning Styles ◽  
Learning Style ◽  
Adaptive Learning ◽  
Student Assessment ◽  
Assessment Method ◽  
Assessment Model ◽  
Clustering Methods ◽  
Proposed Model ◽  
Data Driven Approach

<p>Adaptive learning is one of the most widely used data driven approach to teaching and it received an increasing attention over the last decade. It aims to meet the student’s characteristics by tailoring learning courses materials and assessment methods. In order to determine the student’s characteristics, we need to detect their learning styles according to visual, auditory or kinaesthetic (VAK) learning style. In this research, an integrated model that utilizes both semantic and machine learning clustering methods is developed in order to cluster students to detect their learning styles and recommend suitable assessment method(s) accordingly. In order to measure the effectiveness of the proposed model, a set of experiments were conducted on real dataset (Open University Learning Analytics Dataset). Experiments showed that the proposed model is able to cluster students according to their different learning activities with an accuracy that exceeds 95% and predict their relative assessment method(s) with an average accuracy equals to 93%.</p>

The influence of learning style on satisfaction and learning effectiveness in the asynchronous web-based learning system

2017 ◽  
Vol 35 (4) ◽  
pp. 473-489 ◽  
Author(s):  
Fei-Fei Cheng ◽  
Chui-Chen Chiu ◽  
Chin-Shan Wu ◽  
Der-Chian Tsaih
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Learning System ◽  
Learning Effectiveness ◽  
Web Based ◽  
Content Type ◽  
Web Based Learning ◽  
Significant Difference ◽  
E Learning ◽  
The Web

Purpose The purpose of this paper is to investigate the effect of user’s learning style (including accommodators, divergers, convergers, and assimilators) on user’s satisfaction on the web-based learning system and their learning effectiveness. Design/methodology/approach This experimental research used the college students from a technology institute in Taiwan as the subject sources. By using the Kolb’s learning style model, the students are classified as four types of learners: convergers, divergers, assimilators, and accommodators. The authors analyzed the relationships among the different learning styles with their effectiveness of learning and satisfaction of using the web-based learning system. The mediation effect of gender is also presented. Findings This research indicates that: first, the satisfaction of the web-based learning system has significant influence on the learning performance of learners; second, different learning styles learners have no significant effect to the satisfaction on using the web-based learning system; third, learning effectiveness has significant difference among different learning style learners on the web-based learning system; the learning effectiveness of accommodators and divergers was significantly higher than the assimilators; fourth, different learning styles learners show significant difference in gender proportion. In addition to accommodators, whose proportion of women is higher than men, the other three learning styles’ proportions in men are higher than women. Research limitations/implications This study was grounded in the Kolb’s learning style theory. The authors provide implications for academic studies in e-learning research stream that aimed at understanding the role of learning style as well as gender differences in the asynchronous web-based learning system. Practical implications Results from this study provided the implications for students, educators, and e-learning system designers. The design of teaching materials as well as functions of e-learning systems should take learners’ learning style into consideration to ensure the best learning outcome. Originality/value This study examined the students’ learning style as well as gender differences in the asynchronous web-based learning system. An experiment was conducted to ensure the data were collected in a controlled environment, thus, offer the value that most of the prior study lacks.

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